curriculum
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curriculum [2018/09/18 14:56] cani [Transvere courses and projects (September 2018 to March 2019)] |
curriculum [2019/03/04 22:27] cani [Scientific courses, period 1 (October - December 2018)] |
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| **INF633 - Advanced 3D Graphics (24h, 2 ECTS), Marie-Paule Cani (EP), Julien Pettré (Inria), Pierre Ecormier (EP)** (contact: Marie-Paule.Cani@polytechnique.edu) | **INF633 - Advanced 3D Graphics (24h, 2 ECTS), Marie-Paule Cani (EP), Julien Pettré (Inria), Pierre Ecormier (EP)** (contact: Marie-Paule.Cani@polytechnique.edu) | ||
| - | Computer graphics tackles the creation of 3D contents, from object prototypes to animated scenes. The course will present recent advances in the area. We will cover interactive content creation based on smart geometric models embedding knowledge, the design of layered models for the efficient simulation of natural phenomena and novel, expressive techniques for creating and populating animated virtual worlds. | + | Computer graphics tackles the creation of 3D contents, from object prototypes to animated scenes. This course will focus on the interactions between Computer Graphics and Artificial Intelligence, which recently lead to a number of advances. In particular, we will cover "Creative AI", ie. how interactive content creation can be enhanced using smart graphical models embedding knowledge, as well as the combination of 3D Graphics, AI and learning for the animation of virtual, autonomous creatures. |
| **INF634 - Computer Vision (24h, 2 ECTS), Renaud Keriven (EP & Bentley systems)** (contact: Renaud.Keriven@bentley.com) | **INF634 - Computer Vision (24h, 2 ECTS), Renaud Keriven (EP & Bentley systems)** (contact: Renaud.Keriven@bentley.com) | ||
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| ==== Scientific Courses, period 2 (January - March 2019) ==== | ==== Scientific Courses, period 2 (January - March 2019) ==== | ||
| - | **MAP641 - Reinforcement Learning (48h, 5 ECTS), Odalric-Ambrym Maillard (Inria Lille), Bruno Scherrer (Inria), Olivier Pietquin (Google Brain) ** (contact: odalricambrym.maillard@inria.fr) | + | **MAP641 - Reinforcement Learning (48h, 5 ECTS), Odalric-Ambrym Maillard (Inria Lille), Bruno Scherrer (Inria Nancy), Olivier Pietquin (Google Brain) ** (contact: odalricambrym.maillard@inria.fr) |
| Reinforcement learning aims at finding at each step of a process the best action to take in order to minimize some regret function. This course will introduce the general notions of reinforcement learning and will present several online algorithms that can be used in real-time to take actions. The specificity and the performance of the different algorithms will be discussed in detail. | Reinforcement learning aims at finding at each step of a process the best action to take in order to minimize some regret function. This course will introduce the general notions of reinforcement learning and will present several online algorithms that can be used in real-time to take actions. The specificity and the performance of the different algorithms will be discussed in detail. | ||
curriculum.txt · Last modified: 2023/06/22 18:41 by scornet
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